Probabilistic ontologies and probabilistic ontology learning: significance and challenges
Human knowledge is limited therefore some information is incomplete or contradictory. When we develop an ontology, using an automatic ontology learning system or by human, with such information, the ontology would be inconsistent or we need to manage uncertain information. In non probabilistic appro...
保存先:
主要な著者: | , |
---|---|
フォーマット: | Conference or Workshop Item |
出版事項: |
2011
|
主題: | |
オンライン・アクセス: | http://eprints.utm.my/id/eprint/46173/ http://dx.doi.org/10.1109/icriis.2011.6125727 |
タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
要約: | Human knowledge is limited therefore some information is incomplete or contradictory. When we develop an ontology, using an automatic ontology learning system or by human, with such information, the ontology would be inconsistent or we need to manage uncertain information. In non probabilistic approach, system discovers inconsistencies and then eliminates some parts of ontology to make it consistent. On the other hand, in probabilistic approach, discrepancies are adapted in the ontology. |
---|